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Richard Zemel

Richard Zemel’s research focuses on various aspects of machine learning, particularly unsupervised learning, boosting, and probabilistic networks. He studies applications such as image segmentation and collaborative filtering. He is also interested in neural coding, and has spent quite a bit of time working in the areas of perceptual learning, motion perception and visual attention.

Awards

New Opportunities Award, Canada Foundation for Innovation, 2002-2007.

Young Investigator Award, Office of Naval Research, 1998-2002.

National Sciences and Engineering Research Council Postgraduate Scholarship, 1989-1991.

Discovery Accelerator Supplement, National Sciences and Engineering Research Council